Creating a bunch of test files, and then logging then into mlflow experiment

artifact_viewer_filetypes.py

import json
import plotly.express as px
import mlflow
import requests
    
### prepare sample files to log
# test data
df = px.data.iris()

# sample CSV file
df.to_csv("1_data_sample.csv")

# sample pandas HTML file
df.to_html("2_data_sample.html")

# sample image
r = requests.get("https://upload.wikimedia.org/wikipedia/en/7/7d/Lenna_%28test_image%29.png")
with open("3_image_sample.png", 'wb') as f:
    f.write(r.content)
    
# sample gif
r = requests.get("https://media1.giphy.com/media/bU3YVJAAXckCI/giphy.gif")
with open("4_gif_sample.gif", 'wb') as f:
    f.write(r.content)

# sample plotly plot - HTML
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species", marginal_y="rug", marginal_x="histogram")
fig.write_html("5_plot_sample.html")

# sample geojson
with open("6_map_sample.geojson", "w+") as f:
    data = requests.get("https://gist.githubusercontent.com/wavded/1200773/raw/e122cf709898c09758aecfef349964a8d73a83f3/sample.json").json()
    f.write(json.dumps(data))
    
### log files to mlflow experiment
with mlflow.start_run(experiment_id=1, run_name="file_display") as run:
    
    mlflow.log_param("parameter","test")
    mlflow.log_metric("the_answer",42.0)
    
    mlflow.log_artifact("./1_data_sample.csv")
    mlflow.log_artifact("./2_data_sample.html")
    mlflow.log_artifact("./3_image_sample.png")
    mlflow.log_artifact("./4_gif_sample.gif")
    mlflow.log_artifact("./5_plot_sample.html")
    mlflow.log_artifact("./6_map_sample.geojson")